This paper investigates the execution of classical pseudorandom number generators (PRNGs) on quantum hardware, focusing on their behavior within the qBraid quantum computing platform. Although classical PRNGs such as the Mersenne Twister, LCG, and Blum-Blum-Shub are well-established in cryptographic and simulation applications, their operation in quantum environments has remained largely unexamined. This paper conducts a comprehensive analysis of their statistical and cryptographic performance under quantum-specific constraints, including qubit decoherence, gate noise, and circuit-level errors. The selected PRNGs are modeled and visualized using quantum circuit abstractions, then evaluated for output randomness using NIST SP 800-22 tests and distributional fidelity against uniform and gamma laws. The results reveal varying degrees of robustness among generators when subjected to quantum noise, offering insights into their suitability for hybrid quantum-classical systems. Additionally, their effectiveness is tested in an applied scenario of image encryption, demonstrating the real-world implications of quantum-induced randomness deviations. These findings lay the foundation for designing quantum-aware pseudorandom number generation strategies essential for secure and efficient quantum era applications.
This paper investigates the execution of classical pseudorandom number generators (PRNGs) on quantum hardware, focusing on their behavior within the qBraid quantum computing platform. Although classical PRNGs such as the Mersenne Twister, LCG, and Blum-Blum-Shub are well-established in cryptographic and simulation applications, their operation in quantum environments has remained largely unexamined. This paper conducts a comprehensive analysis of their statistical and cryptographic performance under quantum-specific constraints, including qubit decoherence, gate noise, and circuit-level errors. The selected PRNGs are modeled and visualized using quantum circuit abstractions, then evaluated for output randomness using NIST SP 800-22 tests and distributional fidelity against uniform and gamma laws. The results reveal varying degrees of robustness among generators when subjected to quantum noise, offering insights into their suitability for hybrid quantum-classical systems. Additionally, their effectiveness is tested in an applied scenario of image encryption, demonstrating the real-world implications of quantum-induced randomness deviations. These findings lay the foundation for designing quantum-aware pseudorandom number generation strategies essential for secure and efficient quantum era applications.
ABSTRACT Quantum random number generator (QRNG) platforms use principles of quantum mechanics to create truly random numbers. Traditional pseudo-random number generators (PRNGs) generate numbers based on deterministic formulas. QRNG's use of the principles of superposition and measurement can provide numbers that cannot be predicted or replicated; therefore, they have been used as a source of randomness in various fields. In this research project, an experimental QRNG was designed and built using Qiskit simulations. Each experiment consisted of a series of two-qubit circuits. The circuits were created to place both qubits into an equal probability state. This was done by applying a pair of Hadamard gates (Hadamard gate applies a rotation operator of π/2 radians). Then each circuit was measured. For each measurement, there would be one output from each qubit. Since the Hadamard gate creates an equal-probability superposition, the combination of each qubit will either add up to 1 or subtract from -1. These combinations will be recorded and processed through several methods to evaluate their quality. Those methods include: Shannon Entropy Analysis, Frequency Distribution Analysis and Chi-Square Uniformity Testing. Keywords: Quantum Random Number Generator, Quantum Computing, Quantum Measurement, Cryptography, Secure Randomness, Qiskit Simulation
Generating reliable random and pseudo-random sequences is important in many electronic and signal processing systems, such as secure communications, radar, spread-spectrum methods, and autonomous platforms. Although true and quantum random number generators provide stronger unpredictability, classical pseudo-random number generators, including Linear Feedback Shift Registers (LFSRs) and the Mersenne Twister (MT), are still widely used because they are efficient and easy to implement. This work introduces a user-friendly software platform for generating, analyzing, and evaluating the predictability of pseudo-random bit sequences. The software supports two main functions: generating sequences using classical PRNGs and hybrid combinations, and analyzing input sequences through statistical measures and data-driven methods. In particular, hybrid LFSR-MT structures are studied to examine how they affect sequence complexity and resistance to prediction. The platform also includes machine-learning and deep-learning tools to investigate when deterministic PRNGs may remain partially predictable, even when their structure becomes more complex. The results show that algorithmic random sequence generators have inherent limitations in terms of unpredictability, which supports the use of quantum random sequences in security-critical applications. A comparative study between classical LFSR-MT sequences and quantum random sequences shows that quantum randomness offers higher unpredictability due to its non-deterministic physical origin. The potential use of quantum random sequences in jamming applications is also discussed, highlighting their improved robustness against prediction-based attacks. Overall, the proposed software provides a practical tool for analyzing, comparing, and benchmarking random sequence generators in modern electronic, sensing, and quantum-enabled communication systems.
Quantum computing, grounded in the principles of quantum mechanics, has ushered in a new era of intriguing possibilities and fresh scientific insights. In this document, we present an innovative algorithm tailored for the encryption and decryption of images. This algorithm harnesses the quasi-probability values extracted from each state within the quantum system, represented as |ψ〉. These numerical values are seamlessly integrated with conventional data to facilitate image encryption and decryption processes. Our methodology undergoes comprehensive validation and evaluation through extensive simulations performed on the IBM Qiskit Aer simulator. We subject the generated numerical sequence to rigorous statistical scrutiny using the NIST SP 800-22 suite, ensuring its authenticity and reliability. Employing a quantum system comprising 3 qubits and uniform rotation gates, our algorithm produces a dataset consisting of 41,943,040 binary digits. Additionally, we conduct a thorough assessment encompassing both visual and statistical analyses to ascertain the effectiveness and robustness of our proposed algorithm. Furthermore, we emphasize the critical importance of achieving a quasi-probability error rate of 10−6 for real-world implementation, highlighting the practical viability and scalability of our approach. Through comparative analysis and meticulous examination of correlation patterns, our study provides invaluable insights into the distinctive characteristics and efficacy of our encryption scheme.
True randomness is a basic necessity of secure cryptography. This secures the reliability of encryption keys, digital signatures and authentication mechanisms. Classical random number generators based on deterministic algorithms can introduce patterns and decrease reliability. This paper introduces a Quantum True Random Number Generator (QTRNG) takes advantage of the intrinsic unpredictability of quantum mechanics. The proposed quantum circuit usesRY(π/2)andRZ(π/2)rotations to create superposition states like Hadamard operation. These gates control the phase and orientation of qubits on the Bloch sphere yields measurement outcomes are inherently random. The resulting distributions are unbiased and balanced offers a source of true randomness. The quality of the generated bitstrings is verified using statistical tests such as the NIST SP 800-22, SP 800-90 test suites and autocorrelation tests. The measurements show high entropy, uniform distribution and low bias satisfy the basic requirements for cryptographic security. Phase-based quantum operations provide an efficient for producing high-quality quantum randomness facilitates the construction of effective quantum-secure cryptographic systems.
Generating high-quality random numbers is essential for cryptography, statistical simulations, and cybersecurity. While pseudo-random number generators (PRNGs) are computationally efficient, their deterministic nature introduces potential security vulnerabilities. Recent research has explored chaotic systems as entropy sources due to their sensitivity to initial conditions-a key property for randomness generation. An emerging direction involves leveraging chaos in quantum systems. This paper proposes a quantum-inspired PRNG based on the Quantum Kicked Rotor (QKR), a well-known model in quantum chaos exhibiting complex dynamics such as dynamical localization. The method simulates the QKR and extracts pseudo-random sequences through momentum basis measurements. The generated sequences are evaluated for statistical quality, including the NIST 800-22 standard, which passed all 15 test. The sequences exhibit strong non-periodicity, a critical property for secure cryptographic applications. The proposed approach combines the unpredictability of quantum chaos with the scalability of classical simulation, offering a practical and efficient alternative for secure random number generation.
Quantum Random Number Generators (QRNGs) exploit intrinsic quantum mechanical randomness and are promising candidates for higher-quality randomness than classical RNGs. However, QRNGs on Noisy Intermediate-Scale Quantum (NISQ) platforms are constrained by decoherence, gate and measurement errors, and limited circuit depth, and the resulting impact on statistical randomness is not yet systematically characterized. This work introduces parameterized quantum random number generator (PQRNG) architectures built from parameterized quantum circuits (PQCs) to improve tunability and expressive power under realistic noise. We study three architectures, PQC-H-CH, H-PQC-CH, and H-CH-PQC, and evaluate their randomness under Transpiler optimization and circuit-level error mitigation as preprocessing steps, using NIST SP 800-22 for statistical validation. Utilizing default NIST settings, PQC-H-CH attains the largest number of fully passing preprocessing configurations (126 combinations passing all 15 tests), compared with 110 for H-PQC-CH and 69 for H-CH-PQC, indicating strong robustness across Transpiler optimization and mitigation settings, and we find that preprocessing choices influence randomness quality more strongly than adjusting NIST test parameters. Overall, these results demonstrate that the proposed approach provides a solid foundation for developing more reliable and practical QRNGs using PQCs in NISQ devices.